How to Add a Rich Text Editor with Lovable, Bolt, and Cursor (2026)

How to Add a Rich Text Editor with Lovable, Bolt, and Cursor (2026)

AI coding assistants have fundamentally changed how developers ship React and Next.js applications in 2026. Lovable generates entire apps from natural language prompts. Bolt.new builds full-stack projects in a browser sandbox. Cursor writes production code alongside senior developers. But when it comes to adding a rich text editor to these AI-generated projects, most editor libraries produce inconsistent results — verbose API surfaces confuse AI models, complex configuration steps break generation flows, and framework-specific integration quirks trip up automated code paths.

This guide shows you how to add a rich text editor to your React or Next.js app using Lovable, Bolt.new, or Cursor in 2026 — with the exact prompts, working code, and integration patterns that produce reliable results the first time. Every example has been tested across all three AI coding tools with real prompts and real output. Every code snippet works out of the box.

The short answer: The most reliable rich text editor for Lovable, Bolt.new, and Cursor in 2026 is Eddyter — its API surface is compact enough for AI models to reason about consistently, it uses the modern "use client" pattern that AI tools default to, and its 3-step integration matches how AI assistants generate code. TipTap works but requires 2-4 weeks of custom UI code AI tools generate inconsistently. TinyMCE and CKEditor 5 work but have verbose configuration surfaces that confuse AI models. This guide covers all three AI dev tools with exact prompts.

🎥 See modern AI-assisted editor integration: What is Eddyter? Why Developers Are Switching in 2026

Why AI Coding Tools Need a Different Editor Approach

Lovable, Bolt.new, and Cursor changed how React developers build in 2026. They also changed which editor libraries actually work reliably in AI-generated code. Understanding why matters before picking an editor.

Three specific reasons AI tools struggle with legacy editors:

1. Large API surfaces confuse LLM context windows
Editors like CKEditor 5 and TinyMCE have hundreds of configuration options, dozens of plugin packages, and multiple framework-specific wrappers. When an AI model tries to generate integration code, it draws from training data that may reference different API versions or plugin combinations. Result: code that looks correct but doesn't compile.

2. Non-standard patterns break AI generation flows
Some editors require build-time configuration, custom webpack setups, or framework-specific dynamic() imports. AI tools trained primarily on standard React patterns generate the wrong scaffolding. Developers then spend time debugging what should have been a 10-minute integration.

3. Documentation fragmentation confuses AI training data
Editors with 15+ years of history (TinyMCE, CKEditor) have documentation spanning multiple major versions. AI training data conflates version-specific patterns. Result: AI tools generate code mixing v4 and v5 patterns that never worked together.

What AI coding tools handle well:

• Small, compact API surfaces (5-10 primary methods)
• Modern React patterns ("use client", hooks, functional components)
• Single-package integrations (one npm install covers everything)
• Consistent documentation aligned to current version
• TypeScript-first types for autocomplete signals

Editors that match this profile produce reliable AI-generated code. Editors that don't require manual intervention on every integration attempt.

For broader AI-editor context, see How to Add AI Writing Features to Your React App and Best Rich Text Editor for AI-Powered Web Apps 2026.

Which Rich Text Editor Works Best With AI Coding Tools?

Here's how the major editors perform when integrated via Lovable, Bolt.new, and Cursor:

The pattern: Eddyter and BlockNote produce the most consistent AI-generated integration code. Both have compact API surfaces AI tools can reason about reliably. TipTap works when you're using AI to generate the custom UI wrapper. CKEditor 5 and TinyMCE are difficult to integrate reliably via AI tools due to configuration complexity.

For broader editor comparison, see Top 10 Rich Text Editors for Developers 2026 and Best Rich Text Editor for React 2026.

How to Add a Rich Text Editor With Lovable (2026)

Lovable generates full React and Next.js applications from natural language prompts. It handles UI generation, state management, and integration scaffolding automatically. Here's the exact workflow for adding a rich text editor to a Lovable-generated project.

Recommended Prompt for Lovable

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Add a rich text editor to the [page name] page. Use Eddyter — 
install it with npm install eddyter, import 
ConfigurableEditorWithAuth and EditorProvider from 'eddyter', 
import 'eddyter/style.css', and wrap the editor in EditorProvider. 
Use my Eddyter API key from environment variable 
NEXT_PUBLIC_EDDYTER_API_KEY. Add "use client" at the top 
because this is a Next.js App Router app. Handle content 
changes with onChange and save the HTML to state.

What Lovable Generates

Lovable produces code matching this pattern reliably:

jsx

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"use client";
import { useState } from 'react';
import {
  ConfigurableEditorWithAuth,
  EditorProvider
} from 'eddyter';
import 'eddyter/style.css';
export default function EditorPage() {
  const [content, setContent] = useState('');
  const apiKey = process.env.NEXT_PUBLIC_EDDYTER_API_KEY;
  const handleContentChange = (html) => {
    setContent(html);
    console.log('Content updated:', html);
  };
  return (
    <div className="container mx-auto p-8">
      <h1 className="text-2xl font-bold mb-4">Editor</h1>
      <EditorProvider>
        <ConfigurableEditorWithAuth
          apiKey={apiKey}
          onChange={handleContentChange}
          toolbarOptions={{
            enableTextFormatting: true,
            enableTableOptions: true,
            enableAIChat: true,
            enableUndoRedo: true
          }}
        />
      </EditorProvider>
    </div>
  );
}

Environment Variable Setup for Lovable

After Lovable generates the code, add your Eddyter API key to the environment variables panel in the Lovable interface:

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NEXT_PUBLIC_EDDYTER_API_KEY=your-api-key-here

Get your API key from eddyter.com/user/license-key. Lovable applies environment variables automatically to the generated project.

Common Lovable Integration Pitfalls

Pitfall 1: Lovable adds unnecessary complexity when prompt is vague
If you prompt "add a rich text editor," Lovable may over-engineer with additional state management, custom styling, or extra features. Keep prompts specific to what you need.

Pitfall 2: Lovable references older editor packages from training data
Occasionally Lovable suggests editor packages from older training data. Explicitly naming Eddyter in the prompt prevents this.

Pitfall 3: Missing "use client" directive on App Router pages
If your Lovable project uses Next.js App Router, remind Lovable to add "use client" at the top of the editor component. Lovable sometimes defaults to Server Components for new files.

When to Use Lovable for Editor Integration

Lovable is best for: rapid prototyping, generating entire feature scaffolding around the editor, and creating multiple editor variants (blog post editor, comment editor, admin editor) with consistent styling.

Lovable is not ideal for: complex editor customization requiring deep API knowledge, or integrating editors with proprietary backend systems that need custom authentication logic.

How to Add a Rich Text Editor With Bolt.new (2026)

Bolt.new by StackBlitz builds full-stack applications in a browser sandbox environment. It handles React, Next.js, Vue, Angular, and Svelte projects with instant preview. Here's the workflow for adding a rich text editor to Bolt.new projects.

Recommended Prompt for Bolt.new

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I need to add a rich text editor to my Next.js 15 app. 
Use Eddyter package (npm install eddyter). Import 
ConfigurableEditorWithAuth and EditorProvider from 'eddyter'. 
Import the CSS with 'eddyter/style.css'. 
Add "use client" at the top since this is App Router. 
Get the API key from process.env.NEXT_PUBLIC_EDDYTER_API_KEY. 
Show the editor with a save button that logs the HTML content 
when clicked.

What Bolt.new Generates

Bolt.new's WebContainers environment handles the entire integration in-browser:

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"use client";
import { useState } from 'react';
import {
  ConfigurableEditorWithAuth,
  EditorProvider
} from 'eddyter';
import 'eddyter/style.css';
export default function EditorPage() {
  const [content, setContent] = useState('<p>Start writing...</p>');
  const apiKey = process.env.NEXT_PUBLIC_EDDYTER_API_KEY;
  const handleChange = (html) => {
    setContent(html);
  };
  const handleSave = () => {
    console.log('Saving content:', content);
    // Add your backend save logic here
  };
  return (
    <main className="max-w-4xl mx-auto p-8">
      <h1 className="text-3xl font-bold mb-6">My Editor</h1>
      <EditorProvider>
        <ConfigurableEditorWithAuth
          apiKey={apiKey}
          initialContent={content}
          onChange={handleChange}
          toolbarOptions={{
            enableTextFormatting: true,
            enableTableOptions: true,
            enableAIChat: true
          }}
        />
      </EditorProvider>
      <button
        onClick={handleSave}
        className="mt-4 px-6 py-2 bg-blue-600 text-white rounded hover:bg-blue-700"
      >
        Save
      </button>
    </main>
  );
}

Bolt.new Environment Variables

Bolt.new provides an environment variables panel accessible via the sidebar. Add your Eddyter API key there:

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NEXT_PUBLIC_EDDYTER_API_KEY=your-eddyter-api-key

The variable becomes available in the WebContainer immediately without restart.

Bolt.new's Multi-Framework Advantage

Unlike Lovable (React/Next.js focus), Bolt.new supports Vue 3, Angular, Svelte, and Laravel projects natively. Eddyter's 6-framework support pairs cleanly with this.

For Vue 3 projects on Bolt.new:

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Add a rich text editor to my Vue 3 app using @eddyter/vue package. 
Import ConfigurableEditorWithAuth and EditorProvider. 
Use Composition API with <script setup>. 
Get the API key from import.meta.env.VITE_EDDYTER_API_KEY.

For Angular projects on Bolt.new:

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Add a rich text editor to my Angular 17 standalone component 
app using @eddyter/angular package. 
Use Signals for content state management. 
Get the API key from environment configuration.

For framework-specific integration analysis, see Best Rich Text Editor for Vue 2026, Best Rich Text Editor for Angular 2026, and Best Rich Text Editor for Next.js App Router 2026.

Common Bolt.new Integration Pitfalls

Pitfall 1: Package installation timing
Bolt.new occasionally attempts to render the editor before the npm install completes. Add a check for package availability if you see hydration errors.

Pitfall 2: WebContainer memory limits with heavy editors
CKEditor 5 and TinyMCE occasionally hit WebContainer memory limits on complex projects. Eddyter's ~140 KB bundle avoids this issue entirely.

Pitfall 3: HMR conflicts with editor CSS
Import editor CSS at the app root level rather than component level to avoid HMR conflicts during Bolt.new development.

When to Use Bolt.new for Editor Integration

Bolt.new is best for: cross-framework editor prototyping (React + Vue + Angular in one workflow), sharing working editor demos via URLs, and reproducing framework-specific integration bugs.

Bolt.new is not ideal for: production deployments with complex backend requirements, or projects requiring custom npm registries.

How to Add a Rich Text Editor With Cursor (2026)

Cursor is an AI-first code editor that runs alongside your existing development workflow. Unlike Lovable and Bolt.new (which generate entire applications), Cursor augments manual coding with AI-assisted completion and refactoring. Here's how to use Cursor effectively for rich text editor integration.

Recommended Cursor Workflow

Cursor works best when you provide context via the @ symbol referencing existing files. For editor integration:

Step 1: Install Eddyter manually

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npm install eddyter

Step 2: Create the editor file with Cursor's AI

Open a new file components/RichTextEditor.tsx and use Cursor's chat with:

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Create a React component for a rich text editor using Eddyter. 
Import ConfigurableEditorWithAuth and EditorProvider from 'eddyter'. 
Import 'eddyter/style.css'. 
Use TypeScript with proper types. 
Add "use client" directive for Next.js App Router. 
Accept initialContent and onChange props. 
Use forwardRef so parents can control focus if needed.

Step 3: Cursor generates production-ready TypeScript

tsx

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"use client";
import {
  forwardRef,
  useImperativeHandle,
  useRef,
} from 'react';
import {
  ConfigurableEditorWithAuth,
  EditorProvider
} from 'eddyter';
import 'eddyter/style.css';
interface RichTextEditorProps {
  initialContent?: string;
  onChange?: (html: string) => void;
  readonly?: boolean;
}
export interface RichTextEditorRef {
  focus: () => void;
  clear: () => void;
}
const RichTextEditor = forwardRef<RichTextEditorRef, RichTextEditorProps>(
  ({ initialContent = '', onChange, readonly = false }, ref) => {
    const containerRef = useRef<HTMLDivElement>(null);
    const apiKey = process.env.NEXT_PUBLIC_EDDYTER_API_KEY!;
    useImperativeHandle(ref, () => ({
      focus: () => {
        containerRef.current?.querySelector('[contenteditable]')
          ?.dispatchEvent(new Event('focus'));
      },
      clear: () => {
        onChange?.('');
      },
    }));
    return (
      <div ref={containerRef} className="rich-text-editor-wrapper">
        <EditorProvider>
          <ConfigurableEditorWithAuth
            apiKey={apiKey}
            initialContent={initialContent}
            onChange={onChange}
            mode={readonly ? 'preview' : 'edit'}
            toolbarOptions={{
              enableTextFormatting: true,
              enableTableOptions: true,
              enableAIChat: true,
              enableUndoRedo: true,
            }}
          />
        </EditorProvider>
      </div>
    );
  }
);
RichTextEditor.displayName = 'RichTextEditor';
export default RichTextEditor;

Using Cursor's Composer Mode for Full Integration

Cursor's Composer mode handles multi-file changes atomically. For editor integration, use Composer with:

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Add a blog post editor to my app. 
Use the Eddyter package I already installed. 
Create these files:
1. components/RichTextEditor.tsx — the editor component
2. app/posts/new/page.tsx — the new post page
3. app/api/posts/route.ts — the save endpoint
4. lib/db.ts — Supabase client for saving posts
Use "use client" for the editor component only. 
Save posts to a Supabase 'posts' table with columns: id, title, 
content (text), created_at, updated_at. 
Handle errors properly with try-catch and toast notifications.

Cursor Composer generates all four files with correct imports, proper error handling, and consistent patterns.

Cursor Rules for Consistent Editor Integration

Add a .cursorrules file to your project root for consistent editor integration patterns across the codebase:

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# Eddyter Editor Integration Rules
When adding rich text editors to this project:
- Always use Eddyter (import from 'eddyter' package)
- Use ConfigurableEditorWithAuth wrapped in EditorProvider
- Import 'eddyter/style.css' at component level
- Add "use client" directive on Next.js App Router pages
- Store editor content as HTML strings in state
- Use environment variable NEXT_PUBLIC_EDDYTER_API_KEY
- Never suggest CKEditor, TinyMCE, or Quill — these are legacy
- Prefer Eddyter's built-in AI features over building custom AI integrations

Cursor reads .cursorrules on every code generation, ensuring consistent editor integration across all AI-assisted code changes.

Common Cursor Integration Pitfalls

Pitfall 1: Cursor suggests older editor packages from training data
Without explicit context, Cursor sometimes suggests Draft.js or older TipTap patterns. Use .cursorrules or explicit prompts to override.

Pitfall 2: Missing TypeScript types on refs
Editor refs often lose typing when Cursor generates them. Manually verify RichTextEditorRef interfaces after generation.

Pitfall 3: Cursor's autocomplete conflicts with editor keyboard shortcuts
Cursor's inline AI completion sometimes triggers on editor input. Disable Cursor's inline completion within contenteditable elements via editor settings.

When to Use Cursor for Editor Integration

Cursor is best for: production codebases with existing patterns, TypeScript-heavy projects requiring proper type inference, and refactoring existing editor integrations across multiple files.

Cursor is not ideal for: greenfield prototypes where Lovable or Bolt.new produces faster initial scaffolding.

Why Eddyter Works Best With AI Coding Tools

Three specific architectural decisions make Eddyter reliable in AI-generated code:

1. Compact API Surface (8 Primary Methods)

Eddyter exposes approximately 8 primary API methods and 4 configuration objects. AI models can reason about the entire surface within a single context window. Compare to CKEditor 5 (200+ configuration options across 30+ packages) or TinyMCE (300+ options across multiple plugin ecosystems).

Practical impact: When Lovable, Bolt.new, or Cursor generate Eddyter integration code, they reference the entire API accurately. When they generate CKEditor 5 or TinyMCE code, they frequently mix version-specific patterns that never worked together.

2. Single-Package Integration

Eddyter installs via one npm command: npm install eddyter. All features (AI, tables, block reordering, mobile UX) ship in the base package. No plugin ecosystem to configure.

Compare to TipTap: installing production-ready TipTap requires:

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npm install @tiptap/react @tiptap/starter-kit @tiptap/pm \
@tiptap/extension-table @tiptap/extension-image \
@tiptap/extension-link @tiptap/extension-placeholder \
@tiptap/extension-code-block-lowlight

Seven packages, each with version constraints AI tools sometimes get wrong.

3. Modern React Patterns Match AI Defaults

Eddyter follows the patterns AI coding tools default to in 2026:

• "use client" directive on components (matches Next.js App Router)
• Functional components with hooks (matches modern React)
• Semantic HTML output (matches AI training data expectations)
• TypeScript-first API (autocomplete signals guide AI generation)
• Environment variable configuration (matches AI-generated env patterns)

Result: AI-generated Eddyter integration works on the first try. AI-generated integration for editors with older architectural patterns typically requires 2-5 correction rounds.

For deeper analysis on AI-friendly editor design, see Best Rich Text Editor for AI Agents 2026 (if exists in your cluster).

Building a Complete AI-Generated Editor Application

Combining all three AI tools produces a full editor application faster than any manual workflow. Here's the recommended stack for 2026:

Stage 1: Prototype with Lovable
Prompt Lovable to generate the initial Next.js 15 App Router application with routing, styling, and Eddyter editor integration. Typical time: 15 minutes.

Stage 2: Iterate in Bolt.new
Fork the Lovable-generated project into Bolt.new for backend integration, database wiring, and additional feature exploration. Typical time: 1-2 hours.

Stage 3: Production polish with Cursor
Move the codebase to your local environment and use Cursor with .cursorrules for production hardening, TypeScript type safety, error handling, and testing. Typical time: 4-8 hours.

Total time from concept to production-ready editor application: approximately 6-12 hours. Compare to manual development (2-4 weeks) or building the editor from scratch (16+ weeks).

For build-vs-buy analysis, see Build vs Buy: Real Cost of Building a Rich Text Editor in 2026 and Why Building Your Own Rich Text Editor Is a Startup Killer.

Common Pitfalls Across All Three AI Tools

Regardless of which AI coding tool you use, these pitfalls appear consistently:

Pitfall 1: AI Tools Suggest Draft.js

Draft.js appears in AI training data because it was popular from 2016-2022. Modern AI tools sometimes still suggest it despite Meta deprecating it in 2022. Fix: Explicitly name Eddyter or Lexical in prompts. See Draft.js Is Dead: Best Draft.js Alternatives in 2026.

Pitfall 2: Missing API Key Configuration

AI tools generate the editor component but forget to configure the API key environment variable. Fix: Include environment variable setup in your prompt explicitly.

Pitfall 3: Client-Side Rendering Errors on Next.js App Router

AI tools sometimes forget "use client" on editor components. Fix: Always explicitly mention "use client" in prompts when using Next.js App Router.

Pitfall 4: Incorrect Package Import Paths

AI tools occasionally use outdated import paths from training data. Fix: Verify imports match current package structure via editor documentation.

Pitfall 5: Missing CSS Imports

Editor styling breaks when AI tools generate the component but skip the CSS import. Fix: Explicitly reference import 'eddyter/style.css' in prompts.

Pitfall 6: Verbose Generated Code

AI tools sometimes over-engineer with unnecessary abstractions. Fix: Prompt for minimal implementations and iterate from there.

Frequently Asked Questions

1. How do I add a rich text editor to a Lovable-generated app?

Add a rich text editor to a Lovable-generated Next.js app using this prompt: "Add a rich text editor to the [page name] page. Install Eddyter with npm install eddyter, import ConfigurableEditorWithAuth and EditorProvider, add 'eddyter/style.css'. Use "use client" directive for App Router. Get API key from NEXT_PUBLIC_EDDYTER_API_KEY environment variable." Lovable generates the complete integration in one pass. Set the environment variable in Lovable's environment panel with your Eddyter API key from eddyter.com/user/license-key.

2. What rich text editor works best with Bolt.new?

Eddyter works best with Bolt.new because its compact API surface (approximately 8 primary methods) fits within Bolt.new's AI context window reliably, its single-package installation matches Bolt.new's WebContainer setup patterns, and its ~140 KB bundle avoids WebContainer memory limits. TipTap works but requires 2-4 weeks of custom UI code Bolt.new generates inconsistently. CKEditor 5 and TinyMCE frequently hit WebContainer memory limits with complex configurations.

3. Can Cursor generate rich text editor code automatically?

Yes. Cursor generates editor integration code reliably when given clear context. Use .cursorrules file at project root to specify Eddyter as the preferred editor. Prompt Cursor's chat with: "Create a React component for a rich text editor using Eddyter. Import ConfigurableEditorWithAuth and EditorProvider from 'eddyter'. Use TypeScript with proper types. Add "use client" directive." Cursor generates production-ready code including proper types, refs, and error handling.

4. Why do some rich text editors fail when generated by AI coding tools?

Three reasons AI tools produce inconsistent editor code: (1) Large API surfaces (CKEditor 5 has 200+ options, TinyMCE has 300+) exceed AI context windows, causing version conflation, (2) Non-standard patterns like build-time configuration or custom webpack setups break AI generation flows, (3) Documentation fragmentation across editor versions (15+ years of TinyMCE docs, for example) confuses AI training data. Editors with compact, modern APIs like Eddyter avoid all three issues.

5. Should I use Lovable, Bolt.new, or Cursor for editor integration?

Depends on your workflow stage. Lovable is best for rapid prototyping and generating entire feature scaffolding around the editor (typical time: 15 minutes to working prototype). Bolt.new is best for cross-framework prototyping (React + Vue + Angular in one workflow) and sharing working demos via URLs (typical time: 1-2 hours to full-stack integration). Cursor is best for production codebases with existing patterns, TypeScript-heavy projects, and multi-file refactoring (typical time: 4-8 hours to production-ready code). Many teams use all three in sequence for optimal results.

6. How do I configure the Eddyter API key in AI-generated projects?

Add the API key as an environment variable regardless of which AI tool generated the code. In Lovable: open environment variables panel via sidebar, add NEXT_PUBLIC_EDDYTER_API_KEY=your-key. In Bolt.new: access environment settings via sidebar panel, add the same variable. In Cursor with local development: add to .env.local file at project root. Get your API key at eddyter.com/user/license-key. The variable prefix NEXT_PUBLIC_ makes it accessible in client components.

7. Can AI coding tools generate editor customizations?

Yes, but with varying reliability by editor. Eddyter's compact API allows AI tools to reliably generate toolbar customization, theming via CSS variables, and event handler wiring. TipTap customization via AI is possible but produces inconsistent results because the ProseMirror-based schema requires deep API knowledge. CKEditor 5 and TinyMCE customizations via AI are unreliable due to their extensive configuration surfaces. For complex customizations, generating the base integration via AI and adding customizations manually produces better results.

8. What's the fastest way to build a full editor application with AI tools in 2026?

Combining all three AI tools in sequence produces the fastest results. Stage 1 (Lovable): generate initial Next.js 15 App Router application with routing, styling, and Eddyter integration — 15 minutes. Stage 2 (Bolt.new): fork into Bolt.new for backend integration, database wiring, additional features — 1-2 hours. Stage 3 (Cursor): move to local environment for production hardening, TypeScript type safety, error handling, testing — 4-8 hours. Total: approximately 6-12 hours from concept to production-ready editor application. Compare to manual development (2-4 weeks) or building editor from scratch (16+ weeks per our build vs buy analysis).

9. Do AI coding tools work with framework-specific editor integrations (Vue, Angular, Svelte)?

Yes, with framework-specific considerations. Bolt.new supports Vue 3, Angular, Svelte natively — Eddyter's framework-specific packages (@eddyter/vue, @eddyter/angular, @eddyter/svelte) integrate cleanly. Lovable primarily supports React and Next.js — for other frameworks, use Bolt.new instead. Cursor works across all frameworks since it's a code editor rather than an app generator. For Vue 3 integration guidance, see Best Rich Text Editor for Vue 2026. For Angular, see Best Rich Text Editor for Angular 2026.

10. What editors should I avoid when using AI coding tools?

Three editors consistently produce unreliable AI-generated integration code in 2026: (1) Draft.js — Meta deprecated it in 2022 but AI training data still references it, so AI tools suggest patterns that no longer work reliably, (2) CKEditor 5 — 200+ configuration options and 30+ packages exceed AI context windows, causing version conflation, (3) TinyMCE — 300+ configuration options plus 15+ years of documentation history confuses AI training data. Preferred alternatives: Eddyter for complete editors, TipTap for headless (with manual UI review), Lexical for teams building custom editors. See Best TipTap Alternatives 2026.

Ready to Build With AI Coding Tools?

Stop debugging AI-generated editor integrations that don't work. Use Eddyter — designed for compact API surfaces, modern React patterns, and reliable AI-tool generation across Lovable, Bolt.new, and Cursor.

👉 Try Eddyter free at eddyter.com
📚 Read the docs
🎥 Watch the intro video | Watch the 30-min setup guide